Creating Quant Strategies and Indicators with TradingView Pine Script

Why TradingView

TradingView Pine Script Chart Programming

There are many chart analysis tools, but I prefer TradingView for two main reasons.

First, Pine Script. It allows you to create custom indicators and strategies through a programming language that is simple enough for traders with no coding experience. It supports complex conditional logic and multi-timeframe analysis.

Second, Data Coverage. You can view data from global stocks, cryptocurrencies, Forex, futures, and indices all on one platform. Checking correlations — like between BTC and DXY — takes just a few clicks.

Pine Script Basics: Creating Custom Indicators

Moving Average Crossover Indicator

This is a basic strategy signal. When the short-term moving average crosses above the long-term moving average, it signals a buy; crossing below signals a sell.

//@version=6
indicator("MA Crossover Signal", overlay=true)

fast = ta.sma(close, 20)
slow = ta.sma(close, 50)

plot(fast, color=color.blue, linewidth=2)
plot(slow, color=color.orange, linewidth=2)

buySignal = ta.crossover(fast, slow)
sellSignal = ta.crossunder(fast, slow)

plotshape(buySignal, title="Buy", location=location.belowbar, 
color=color.green, style=shape.triangleup, size=size.small)
plotshape(sellSignal, title="Sell", location=location.abovebar, 
color=color.red, style=shape.triangledown, size=size.small)

BTC + DXY Correlation Dashboard

This indicator overlays BTC price and DXY on the same chart to identify inverse relationships and timing entry points.

//@version=6
indicator("BTC vs DXY Correlation", overlay=false)

btc = request.security("BINANCE:BTCUSDT", timeframe.period, close)
dxy = request.security("TVC:DXY", timeframe.period, close)

// 20-day correlation
corr = ta.correlation(btc, dxy, 20)

plot(corr, color=corr > 0 ? color.red : color.green, linewidth=2)
hline(0, color=color.gray, linestyle=hline.style_dashed)
hline(0.5, color=color.new(color.red, 80))
hline(-0.5, color=color.new(color.green, 80))

Connecting Pine Script Strategies to Python Backtesting

While Pine Script’s strategy mode enables simple backtests, complex validation techniques like Walk-forward analysis and accounting for trading costs are better handled in Python.

Workflow

Rapid prototyping of strategies in Pine Script on TradingView.
If promising, port the same logic to Python (Backtrader, QuantConnect).
Perform rigorous validation in Python, including Walk-forward, Purged K-Fold, etc.
Upon passing validation, connect to live trading APIs (e.g., IBKR).

Example: Transferring Pine Script to Python

import pandas as pd
import numpy as np

def ma_crossover_signal(df: pd.DataFrame, fast: int = 20, slow: int = 50):
    """Translate Pine Script MA Crossover to Python"""
    df['fast_ma'] = df['close'].rolling(fast).mean()
    df['slow_ma'] = df['close'].rolling(slow).mean()
    
    df['signal'] = 0
    df.loc[df['fast_ma'] > df['slow_ma'], 'signal'] = 1   # Buy
    df.loc[df['fast_ma'] < df['slow_ma'], 'signal'] = -1  # Sell
    
    # Extract crossover points
    df['trade'] = df['signal'].diff().abs() > 0
    return df

TradingView Free vs Paid Plans

Features	Free	Essential ($12.95/month)	Plus ($24.95/month)	Premium ($49.95/month)
Indicators per Chart	2	5	10	25
Supported Timeframes	Basic only	Add seconds	Same	Same
Alerts	5	20	100	400
Saved Layouts	1	5	10	Unlimited
Server-side Alerts	✗	✓	✓	✓
Pine Script Strategy	Basic	Same	Same	Same

For quant researchers: Essential plan is sufficient. Most analyses are possible with 5 indicators, and server-side alerts enable automatic notifications.

Premium is needed if you want to monitor multiple strategies simultaneously or analyze data at sub-minute intervals.

BTC Analysis Layout Setup

I use a 4-panel layout for BTC analysis:

Top-left: BTC/USDT 4-hour candles — Harmonic patterns + MA crossover
Top-right: DXY daily — Dollar strength/weakness trend
Bottom-left: BTC Funding Rate (Bybit/Binance)
Bottom-right: BTC vs DXY correlation indicator

This setup allows monitoring price, macro factors, derivatives, and correlations all on one screen.

Summary

Use TradingView for quick idea visualization and initial validation. For rigorous backtesting and live deployment, transfer logic to Python.

The most practical quant workflow is: Pine Script → Python porting → Walk-forward validation → live trading integration.

Sign up for TradingView — Discount available through this referral link.